https://github.com/phanchenh/pwc_powerbi_job_simulation
https://github.com/phanchenh/pwc_powerbi_job_simulation
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/phanchenh/pwc_powerbi_job_simulation
- Owner: PhanChenh
- Created: 2025-02-24T03:32:13.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-02-24T03:34:21.000Z (3 months ago)
- Last Synced: 2025-02-24T04:27:54.587Z (3 months ago)
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- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Project Title: PwC Power BI Job Simulation
## Table of Contents
- [Overview](#overview)
- [Dataset](#dataset)
- [Objective](#objective)
- [Analysis Approach](#analysis-approach)
- [Key Findings](#key-findings)
- [How to run code](#how-to-run-code)
- [Technologies Used](#technologies-used)
- [Results & Visualizations](#results--visualizations)
- [Recommendation](#recommendation)
- [Contact](#contact)
## Overview
The PwC Power BI Job Simulation, completed through the Forage platform, provided a hands-on opportunity to develop and demonstrate data analysis and visualization skills. The simulation involved analyzing call center data, customer retention metrics, and diversity and inclusion statistics for a telecom client, using Power BI to generate actionable insights.
## Dataset
The project utilized the following datasets:
- Call Center Dataset: Containing metrics on customer satisfaction, call volume, and agent performance.
- Customer Retention Dataset: Including demographic data, contract types, service subscriptions, and churn status.
- Diversity & Inclusion Dataset: Featuring gender balance, promotion rates, and employee turnover statistics.
## Objective
The primary objectives of this project included:
- Developing a Power BI dashboard to visualize call center performance metrics.
- Identifying trends and factors contributing to customer churn in the telecom industry.
- Analyzing HR data to provide insights on gender diversity and inclusion within the organization.
## Analysis Approach
The analysis was conducted in three main tasks:
- Call Center Analysis: Created an interactive dashboard to visualize KPIs such as customer satisfaction, calls answered/abandoned, call volume trends, and agent performance.
- Customer Retention Analysis: Built a dashboard to identify key drivers of customer churn and proposed proactive strategies to improve retention.
- Diversity & Inclusion Analysis: Analyzed gender-related KPIs and provided recommendations to address gender balance challenges at the executive level.
## Key findings
Call Center Performance:
- Average speed to answer: 67.52s, average talk duration: 3m 45s, with 81.08% of calls answered.
- Most agents meet performance benchmarks, with average answer speed around 66-70s and call resolution at ~72-73%.
- Satisfaction rating is moderate at 3.4/5, and only 27.08% of calls are unresolved.
Customer Return & Risk Analysis:
- High churn rate of 26.54%, with month-to-month contracts showing the highest churn (42.7%).
- Electronic check payment method has the highest churn rate among all methods.
- Fiber optic service also shows a high churn rate of 41.9%.
Diversity & Inclusion:
- Female employees perform slightly better (2.42 vs. 2.41 for males).
- Lower promotion rates for women at higher job levels.
- Women are promoted faster than men in most roles, except at the executive and director levels.
- Turnover rate is 10%, with male-dominated exits in strategy and HR.
## How to run code
1. Load the Dataset: Import the dataset by loading the files from the repository
2. Loading the dashboard (pbix file) in Power BI
- Open Power BI Desktop and go to File > Open to load the existing dashboard from the repository.
## Technologies Used
- Power BI: Created interactive dashboards with charts, graphs, and slicers to visualize KPIs for call center performance, customer retention, and diversity & inclusion.
- DAX (Data Analysis Expressions): Calculated key metrics like customer satisfaction, call handling performance, and churn prediction.
## Results & Visualizations
Interactive dashboard: [PwC_PoweBI_Job_Simulation_Call_Center_Analysis](https://app.powerbi.com/view?r=eyJrIjoiMWQ5NmQ1NmItNzIxNC00NmJlLWJjNmQtNDRiNTU2ZDZmZTI5IiwidCI6IjFkYTAyNjFjLTQ1ZjktNGI5MS04N2JiLTlkMGUzNzJlMmYwNiJ9)
Interactive dashboard: [PwC_PoweBI_Job_Simulation_Customer_Retention_Analysis](https://app.powerbi.com/view?r=eyJrIjoiMDY3N2E3NGQtMWUwMC00ZWY2LTkyNGEtNWYzNmRlYjZhZDgwIiwidCI6IjFkYTAyNjFjLTQ1ZjktNGI5MS04N2JiLTlkMGUzNzJlMmYwNiJ9)
Interactive dashboard: [PwC_PoweBI_Job_Simulation_Diversity_&_Inclusion_Analysis](https://app.powerbi.com/view?r=eyJrIjoiOGIxZjE0YWQtNDRlMy00NmFiLTgzYmItOWZiOGUzNjIzNmExIiwidCI6IjFkYTAyNjFjLTQ1ZjktNGI5MS04N2JiLTlkMGUzNzJlMmYwNiJ9)
Figure 1: Call Center Trend Dashboard
Finding:
- Visualized KPIs: call answer rates, resolution rates, satisfaction scores, and agent performance metrics.
- Trends show consistent agent performance but room for improvement in customer satisfaction.
Figure 2: Customer Return Analytics
Figure 3: Customer Risk Analytics
Finding:
- Month-to-month contracts and electronic check payments have high churn.
- Fiber optic service retention needs attention.
Figure 4: HR Analytics 1
Figure 5: HR Analytics 2
Finding:
- Gender distribution by department and job level highlights promotion disparities.
- Performance by gender and department suggests strategic roles need balanced gender representation.
## Recommendation
For Call Center:
- Implement training to boost call resolution rates and satisfaction scores.
- Monitor underperforming agents and provide targeted coaching.
For Customer Retention:
- Offer incentives for long-term contracts to reduce month-to-month churn.
- Introduce targeted retention strategies for customers using electronic check payments and fiber optic services.
For Diversity & Inclusion:
- Address gender disparities in promotions, especially at higher job levels.
- Implement mentorship programs to support career growth for underrepresented groups.
## Contact
📧 Email: [email protected]
🔗 [LinkedIn](https://www.linkedin.com/in/phan-chenh-6a7ba127a/) | Portfolio